Researchers at the French National Center for Scientific Research (CNRS) have developed a mathematical model for more accurately predicting race times from smartwatches.
Most smartwatch measurements of VO2 max (the maximum rate at which runners consume oxygen during exercise) from heart rate readings are inaccurate, and can lead to errors of up to 20%.
The CNRS team's model employs smartwatch data to calculate a runner's speed at maximum oxygen uptake, and the rate at which they lose power during a race.
The researchers tested the model with smartwatch data from about 14,000 runners, and could predict people's marathon times to within an average 10% of actual time (and to within less than 5% of actual time for elite athletes).
Lukasz Malek at Poland's National Institute of Cardiology said more accurate race-time predictions could potentially lower the risk of overtraining, as well as "the risk of potentially life-threatening incidents."
From New Scientist
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